Unable to load .mpt file (EIS imported)

[KamilBUT]

I am unable to load .mpt file which was previously imported to EC-Lab from .txt hence has no cycle_number column:

---

AttributeError Traceback (most recent call last)
in
1 from PyEIS import *
2
----> 3 ex1 = EIS_exp(path='EIS/', data=['Imported_EIS.mpt'])

~\miniconda3\lib\site-packages\PyEIS\PyEIS.py in init(self, path, data, cycle, mask)
2241 print('Data file(s) could not be identified')
2242
-> 2243 self.cycleno.append(self.df_raw0[j].cycle_number)
2244 if np.min(self.cycleno[j]) <= np.max(self.cycleno[j-1]):
2245 if j > 0: #corrects cycle_number except for the first data file

~\miniconda3\lib\site-packages\pandas\core\generic.py in getattr(self, name)
5272 if self._info_axis._can_hold_identifiers_and_holds_name(name):
5273 return self[name]
-> 5274 return object.getattribute(self, name)
5275
5276 def setattr(self, name: str, value) -> None:

AttributeError: 'DataFrame' object has no attribute 'cycle_number'

Imported_EIS.txt

If I manually add this column, I am greeted with another error, similar to the error I will discuss in next issue topic.

[n-bock]

Hi, does the tutorial work for you?

import PyEIS
ex1 = PyEIS.EIS_exp(path='https://raw.githubusercontent.com/kbknudsen/PyEIS/master/Tutorials/data/', data=['ex1.mpt'])
```

[KamilBUT]

Yes, it does.
I don't have problems with tutorials .mpt even in my customized code. In this case, there is a problem in EIS_exp function because it's expecting there is a cycle_number column in the .mpt file, which in this case there is not.

You can try to use my EIS. I have attached the file (but had to change it to .txt)

[n-bock]

Okay, I just submitted a pull request (you can also fetch the master branch from my fork: n-bock/PyEIS) which should help with your issue. You have to modify your text file like this: ex3.txt or you adapt PyEIS_Data_extraction.py line 153ff so they match your txt-file header.

[KamilBUT]

I was trying to add some predefined arguments to the function as Z_Re='string', Z_Im='string' so it could be easily modified.
Unfortunately, when I tried to call even your original extract_csv function it didn't separate columns at all, however, when I implemented the same thing directly to Jupyter notebook it worked correctly. Dunno why...